The success of AutoMindr depends on the learning outcomes of novice car maintainers. By prompting users at the appropriate times and locations to gather information or their car’s status, users are more likely to follow through with the prompt. This results in a much more intuitive process where users do not have to fit car maintenance learning activities into their schedules. Instead, AutoMindr fits the activities in for them. Because users will be thinking about their car often, it is likely that car maintenance skills will become a part of the user’s procedural memory and long-term memory. Hopefully, the result here is that the user will gain these car maintenance habits as second nature. The prompt tool should act as a virtual tutor with three parts:
For example, a user is prompted to remember to check their tire treads. The prompt will then ask if the user knows how to do this. If the the response is yes, the prompt goes away and the user can easily get to the task at hand, meaning low overhead for advanced users. If the user says no, they will be presented with a just-on-time tutorial explaining how to check the tire tread. The third part of the prompt, regardless of a yes or no answer, will provide motivation as to why the specific maintenance task is important. The prompt can give motivation in several areas including monetary, safety, and behavior modeling (usually modeled after advanced maintainers) reasons. For example, a safety motivation in our tire tread exercise would explain how low tire tread means less grip on the road resulting in a higher chance of slipping in the rain which could cause an accident. In addition to teaching the user through the prompt system, buddies can also teach each other. For example, a buddy can share a narrative regarding a personal situation with a specific action of car maintenance. In our observations, one of our subjects had a story about he did not replace his tires on time and got into an accident on the expressway. Through the game, buddies of this user could read his personal narrative. This may be either online, or through the prompt motivation. We will need to give users an incentive to provide stories and an incentive to read stories. If we can accomplish this, then a user can be motivated to learn a new skill based on real-life situations of their friends. By connecting new learning with knowledge already known, such as knowledge in your social life, meaningful learning can occur.
Teaching Tool
The success of AutoMindr depends on the learning outcomes of novice car maintainers. By prompting users at the appropriate times and locations to gather information or their car’s status, users are more likely to follow through with the prompt. This results in a much more intuitive process where users do not have to fit car maintenance learning activities into their schedules. Instead, AutoMindr fits the activities in for them. Because users will be thinking about their car often, it is likely that car maintenance skills will become a part of the user’s procedural memory and long-term memory. Hopefully, the result here is that the user will gain these car maintenance habits as second nature.The prompt tool should act as a virtual tutor with three parts:
For example, a user is prompted to remember to check their tire treads. The prompt will then ask if the user knows how to do this. If the the response is yes, the prompt goes away and the user can easily get to the task at hand, meaning low overhead for advanced users. If the user says no, they will be presented with a just-on-time tutorial explaining how to check the tire tread.
The third part of the prompt, regardless of a yes or no answer, will provide motivation as to why the specific maintenance task is important. The prompt can give motivation in several areas including monetary, safety, and behavior modeling (usually modeled after advanced maintainers) reasons. For example, a safety motivation in our tire tread exercise would explain how low tire tread means less grip on the road resulting in a higher chance of slipping in the rain which could cause an accident.
In addition to teaching the user through the prompt system, buddies can also teach each other. For example, a buddy can share a narrative regarding a personal situation with a specific action of car maintenance. In our observations, one of our subjects had a story about he did not replace his tires on time and got into an accident on the expressway. Through the game, buddies of this user could read his personal narrative. This may be either online, or through the prompt motivation. We will need to give users an incentive to provide stories and an incentive to read stories. If we can accomplish this, then a user can be motivated to learn a new skill based on real-life situations of their friends. By connecting new learning with knowledge already known, such as knowledge in your social life, meaningful learning can occur.